In our modern information age society, people acquire and deal with a mass of information, which may be represented by data objects, every day. People desire a tool to help them to intuitively, efficiently, and comprehensively grasp the mass of information represented by the data objects, along with an understanding of their attributes and correlations, since the time available for processing the mass of information is limited.
For example, to learn about a certain subject matter and the related information, it is a common measure for people to adopt various well-known Web search engines to obtain a mass of returned information. Typically, the results returned by a search engine, such as Google (http://www.google.com), are displayed on Personal Computer (“PC”) screen, which often have display resolutions of 800×600 1280×1024 pixels, in a one-dimensional ranked index list. Each search result may be regarded as a data object and the user is able to browse through some of the data objects that comprise the search results, t, and see some of the related physical attribute information on a browser page.
As an example, FIG. 6 is a screenshot (1280×1024 pixels) of a display interface for search results returned by the conventional search engine Google, where only seven (7) results are displayed. The user has to operate buttons, mouse or other I/O devices to scroll up and down within the result page or go to a next page, in order to see more search results. Under these conditions, if the desired search result does not appear at the beginning of a ranked list, the time needed for a user to find the satisfying result is greatly increased. The search efficiency is even poorer when the satisfying result does not appear on the first page or in the first few result pages. This is because users often go through several pages of undesired results before a desired one is located. Such a process is also tedious, boring, unreliable and sometimes impractical.
Spatial constraints for presenting search engine results are greatly increased when using electronic devices with limited display surfaces, such as mobile phones, portable digital assistants, and other portable or small-screen electronic devices. In such situations, in order to see all return results for a query, the user often needs to repeatedly interact with the buttons, mouse or other I/O devices.
Some other search engines such as Kartoo (http://www.kartoo.com). Kartoo display a limited number of results comprising data objects using a graph, which merely reflects the relationships among the search results. Consequently, the efficiency of usage of interface space is low. In addition, since Kartoo fails to express the relationships between the rich attributes of data objects in a manner that enable the display of relationship information using multimedia expression methods. Further, because Kartoo also fails to provide a plurality of display methods and interfaces to facilitate human-computer interaction, it cannot satisfy the demand of intuitively, efficiently and comprehensively grasping the mass of information and attribute information thereof.
Another type of search engine, represented by Clusty (http://www.clusty.com), displays categorized information in a text-based, two-dimensional space but lacks a visual interface to express the categorized information. Such a search engine cannot satisfy the demand of intuitively, efficiently, and comprehensively grasping the attribute and correlative information in situations involving a massive number of data objects.
As for other electronic information retrieval systems, they generally return a mass of related data objects by a retrieval component, similar to that of a search engine, when the user inputs a query. The user usually has to analyze a large number of data objects, if not all of them, to find the most desired one(s). It is a laborious and time-consuming process.
All the current display methods for a mass of information exhibit one or more of the following common flaws: (1) they can only display a small number of data objects simultaneously. They can only display a small number of attributes of each data object simultaneously. They do not efficiently utilize the presentation capability of display screens of the devices. For instance, they can only display fewer than twenty search results and a few information attributes of the search results on an 800×600 pixel screen. (2) Because of the limited amount of displayed data objects and their attributes, current methods have no mechanism to intuitively, efficiently, and comprehensively provide the macroscopic information of the search results. Examples of such information are: the number of results from among the top 200 results that are from the U.S.; the number that are from China; the number that are from the domain “edu”; the number that are from the domain “edu” in the U.S. (3) The existing methods do not provide a user with interactive approaches to customize the management of search results beyond the basic operations such as going to another page based on the page number. (4) Because of the limitations of the number of information results and their data object attributes that can be simultaneously displayed and of the simplistic interactions provided, the current display methods cannot comprehensively and intuitively express the relationship among different result documents. For instance, two result documents ranked 12th and 68th might address the same topic, both came from an academic domain, but the result document ranked 12th was published on the Internet several years before the 68th ranked document. Such subtle, complex relationship cannot be expressed using the current display methods for the result information. (5) Current display methods for the result information do not use aural properties to express the attributes of and correlations among the result documents. (6) Because only a limited number of visual properties are used in presentation, current display methods lack the means to provide users with immersive interaction with search results.
From the discussion above, we can see that even though search engines or retrieval tools can assist a user by returning a large number of search results as well as the detailed result attributes, the limitations of existing display means for a mass of information significantly limit a user's ability to intuitively, efficiently and comprehensively grasping the massive number of data objects, their attributes and correlations among the said data objects, and thus prevent users from fully utilizing the rich information available in the result data objects.